data: min [ $partialdiff sub Y$ ( $integral dX$ { UCSB CHIRPS v1p8 dekad prcp } climatology ) anomalies ]

served from maproom.metmalawi.gov.mw

min [ ∂_Y ( ∫dX { UCSB CHIRPS v1p8 dekad prcp } climatology ) anomalies ]: ∂_Y precipitation data

CHIRPS v1p8 dekad prcp int_dX int_dX partial_Y partial_Y ∂_Y precipitation from UCSB: UC Santa Barbara.

Independent Variables (Grids)

Longitude (longitude): grid: /X (degree_east) ordered (180W) to (180) by 0.05 N= 7201 pts :grid

Other Info

CE

null

colorscalename

prcp_dekadrate_max600_smooth

CS

null

datatype

realarraytype

file_missing_value

-9999.0

maxncolor

254

missing_value

NaN

standard_name

lwe_precipitation_rate

units

standard units*

0.001 meter

history

$partialdiff sub Y$ [ $integral dX$ ( UCSB CHIRPS v1p8 dekad prcp ) climatology ]
Averaged over T2[1981, 2357 30 Dec 2023 - 2357 30 Dec 2024] minimum 0.0% data present

$partialdiff sub Y$ [ $integral dX$ ( UCSB CHIRPS v1p8 dekad prcp ) climatology ] climatology

Averaged over T2[1981, 2357 30 Dec 2023 - 2357 30 Dec 2024] minimum 0.0% data present
Averaged over T2=0000 1 Jan 1960 - 0000 1 Jan 1961 minimum 0.0% data present

min [ $partialdiff sub Y$ ( $integral dX$ { UCSB CHIRPS v1p8 dekad prcp } climatology ) anomalies ]

min over Y[49.95N, 49.95S] T[0000 1 Jan - 0000 11 Jan, 0000 21 Dec - 0000 1 Jan]

References

Funk, C. C, Peterson, P. J., Landsfeld, M. F., Pedreros, D. H., Verdin, J. P., Rowland, J. D., Romero, B. E., Husak, G. J. Michaelsen, J. C., and Verdin, A. P., 2014, A quasi-global precipitation time series for drought monitoring: U. S. Geological Survey Data Series 832, 4 p., http://dx.doi.org/110.3133/ds832.

Last updated: Thu, 02 Nov 2023 07:43:25 GMT
Expires: Tue, 01 Jul 2025 00:00:00 GMT

Data Views

	X
min [ $partialdiff sub Y$ ( $integral dX$ { UCSB CHIRPS v1p8 dekad prcp } climatology ) anomalies ][ X \|]	M

Filters

Here are some filters that are useful for manipulating data. There are actually many more available, but they have to be entered manually. See Ingrid Function Documentation for more information.

Monthly Climatology calculates a monthly climatology by averaging over all years.
anomalies calculates the difference between the (above) monthly climatology and the original data.
Integrate along X
Differentiate along X
Take differences along X